Clustering Engine for Product Matching Precision
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Solution Overview
Problem
Existing financial management applications face challenges in effectively matching user-entered product descriptions with relevant products for advertising purposes, particularly due to inexact descriptors, abbreviations, and misspellings, which hinder tailored advertising effectiveness.
Innovation Solution
A system comprising a clustering engine that processes user-entered text strings to generate nodes and edges, sends search queries to a marketplace system, and selects product identifiers based on clustering algorithms to provide targeted advertisements, accounting for variations in user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional exact matching methods are used to match user-entered product descriptions with products, then matching precision is high for exact descriptions, but matching reliability deteriorates when users provide inexact descriptors, abbreviations, or misspellings
Solution Approach 1:
The patent introduces an intermediary component (clustering engine or matching service) that sits between the user's inexact product description and the product database. This intermediary performs fuzzy matching, typo tolerance, and abbreviation expansion to bridge the gap between imprecise user input and accurate product identification, thereby maintaining both precision and reliability
Solution Approach 2:
The system dynamically adjusts matching parameters such as similarity thresholds, weighting factors, and tolerance levels based on the quality and characteristics of user input. When inexact descriptors are detected, the system modifies matching parameters to accommodate variations while still identifying the correct product, thus resolving the contradiction between precision and reliability
2Measurement precision
If the system processes and clusters user-generated text strings to improve matching accuracy, then advertising relevance is improved, but system complexity increases
Solution Approach 1:
The patent divides the complex text processing task into separate modular components: text normalization module, clustering engine, similarity calculation module, and product matching module. Each component handles a specific aspect of the processing pipeline, making the overall system more manageable and maintainable while achieving high matching accuracy through coordinated operation of these specialized segments
3Adaptability or versatility
If the system implements clustering algorithms to handle varied user descriptions, then adaptability to different user inputs is improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary text normalization, tokenization, and feature extraction on user descriptions before applying computationally intensive clustering algorithms. By preprocessing the data to reduce dimensionality and standardize input formats, the system prepares the data in advance, allowing the clustering stage to operate more efficiently with reduced computational energy requirements while maintaining high adaptability
Data Source
AI summary
A method and system for selecting a product to advertise. The method includes receiving an advertisement request from an application, generating a plurality of nodes corresponding to a plurality of user-entered text strings received from a user by the application, sending, to a marketplace system, a plurality of search queries for the plurality of user-entered text strings, and receiving a plurality of product identifier in response to the plurality of search queries. The method further includes determining a plurality of edges corresponding to the plurality of product identifiers, generating a cluster using the plurality of nodes and the plurality of edges, selecting a product identifier of the plurality of product identifiers to obtain a selected product identifier, and providing, to the application, the selected product identifier, wherein the application displays, to the user, an advertisement for the product identified by the product identifier.